apache/iceberg · error · IllegalArgumentException

Encountered an unsupported ORC type during a write from…

Error message

Encountered an unsupported ORC type during a write from Spark.

What it means

SparkOrcWriter.createFieldGetter maps Iceberg/Spark field types to ORC field getter functions. The default branch fires when the column's Iceberg TypeID is not one of the supported ORC-writable types (e.g. a nested or unrecognized type id reached the switch). This is a schema-support guard: the writer cannot produce an ORC encoding for that type.

Solutions

  1. Check the table schema for columns whose Iceberg type is unsupported by this Spark ORC writer version and drop/retype them.
  2. Upgrade the iceberg-spark module to a version matching your Spark release so all types in the schema are supported.
  3. Cast unsupported columns to a supported type (e.g. string/binary) before writing.

Example fix

// before
// writing table with an exotic nested type column
// after
// cast the column to a supported type before writing
df = df.withColumn("col", col("col").cast("string"));
Defensive patterns

Strategy: validation

Validate before calling

// validate all column types are supported before writing
schema.columns().forEach(c -> Preconditions.checkArgument(
    Set.of(BOOLEAN, INT, LONG, FLOAT, DOUBLE, DATE, TIMESTAMP, STRING, BINARY, DECIMAL, FIXED)
        .contains(c.type().typeId()),
    "Unsupported ORC write type: %s", c.type()));

Prevention

When it happens

Trigger: Writing a Spark DataFrame through Iceberg's ORC writer where a column's Iceberg type resolves to a TypeID not handled by createFieldGetter's switch (e.g. an unsupported nested type variant).

Common situations: Using newer or exotic Iceberg types (e.g. unknown/nested types, variant-like types) with an older Spark ORC writer module; schema drift after table evolution where the writer version predates the type.

Understand the failure class

Background: UnsupportedOperationException and "is not supported" errors: when a library deliberately refuses a call — this error's family across 30 libraries.

Related errors

AI-assisted analysis of apache/iceberg@86d9c8fc54 (2026-09-12). Data as JSON: /api/errors/609a7ac7abbdd818. Report an issue: GitHub.

Appendix: source

Thrown at spark/v4.1/spark/src/main/java/org/apache/iceberg/spark/data/SparkOrcWriter.java:221

            (row, ordinal) ->
                row.getDecimal(ordinal, fieldType.getPrecision(), fieldType.getScale());
        break;
      case STRING:
      case CHAR:
      case VARCHAR:
        fieldGetter = SpecializedGetters::getUTF8String;
        break;
      case STRUCT:
        fieldGetter = (row, ordinal) -> row.getStruct(ordinal, fieldType.getChildren().size());
        break;
      case LIST:
        fieldGetter = SpecializedGetters::getArray;
        break;
      case MAP:
        fieldGetter = SpecializedGetters::getMap;
        break;
      default:
        throw new IllegalArgumentException(
            "Encountered an unsupported ORC type during a write from Spark.");
    }

    return (row, ordinal) -> {
      if (row.isNullAt(ordinal)) {
        return null;
      }
      return fieldGetter.getFieldOrNull(row, ordinal);
    };
  }

  interface FieldGetter<T> extends Serializable {

    /**
     * Returns a value from a complex Spark data holder such ArrayData, InternalRow, etc... Calls
     * the appropriate getter for the expected data type.
     *
     * @param row Spark's data representation

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